• DocumentCode
    1794939
  • Title

    Joint tracking and classification on aerodynamic model and RCS by ground-based passive radar

  • Author

    Long Xu ; Kun Zhan ; Hong Jiang ; Liang Bai ; Mengjie Wu

  • Author_Institution
    Sci. & Technol. on Aircraft Control Lab., Beihang Univ., Beijing, China
  • fYear
    2014
  • fDate
    8-10 Aug. 2014
  • Firstpage
    756
  • Lastpage
    761
  • Abstract
    For the ground-based passive radar to monitor low altitude threat targets, the radio frequency modulation (FM) signals transmitted by the broadcast stations is exploited, and an effective joint tracking and classification (JTC) algorithm based on aerodynamic model and radar cross section (RCS) is presented. The aerodynamic equations are used as motion model, and target classification is made possible by the inclusion of RCS in the measurement vector. Thus, tracking and classification are closely coupled, giving full play to the advantages of joint tracking and classification. Our algorithm is implemented by interacting multiple model regularized particle filter (IMMRPF) and simulations show the superiority of our algorithm.
  • Keywords
    frequency modulation; particle filtering (numerical methods); passive radar; radar cross-sections; radar tracking; signal classification; target tracking; aerodynamic equations; aerodynamic model; broadcast stations; ground-based passive radar; interacting multiple model regularized particle filter; low altitude threat targets; motion model; radar cross section; radio frequency modulation; target classification; Aerodynamics; Atmospheric modeling; Particle filters; Passive radar; Radar tracking; Target tracking; Vectors; aerodynamic model; frequency modulation (FM); interacting multiple model regularized particle filter (IMMRPF); joint tracking and classification (JTC); radar cross section (RCS);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Guidance, Navigation and Control Conference (CGNCC), 2014 IEEE Chinese
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4799-4700-3
  • Type

    conf

  • DOI
    10.1109/CGNCC.2014.7007306
  • Filename
    7007306